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ablation_models.md

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Configurations of Ablation Models

Use the following configurations and adapt bash/train.sh to train the ablation models.

Input Representation

  • Our HPTR for Waymo dataset. The model has 15.2M parameters. 
    model=scr_womd \
  • Our HPTR for AV2 dataset. 
    trainer=av2 \
model=scr_av2 \
datamodule=h5_av2 \
  • Agent-centric baseline Wayformer, i.e. WF baseline. 
    model=acg_womd \
  • Scene-centric baseline SceneTransformer, i.e. HPTR SC. 
    model=scg_womd \

Hierarchical Architecture

  • HPTR diag+full with 15.4M parameters. It needs RTX 3090 for training. 
    model.model.intra_class_encoder.n_layer_tf_map=6 \
model.model.intra_class_encoder.n_layer_tf_tl=2 \
model.model.intra_class_encoder.n_layer_tf_agent=2 \
model.model.decoder.tf_n_layer=2 \
model.model.decoder.k_reinforce_tl=-1 \
model.model.decoder.k_reinforce_agent=-1 \
model.model.decoder.k_reinforce_all=1 \
  • HPTR diag with 15.4M parameters. 
    model.model.intra_class_encoder.n_layer_tf_map=6 \
model.model.intra_class_encoder.n_layer_tf_tl=3 \
model.model.intra_class_encoder.n_layer_tf_agent=3 \
model.model.decoder.tf_n_layer=2 \
model.model.decoder.k_reinforce_tl=-1 \
model.model.decoder.k_reinforce_agent=-1 \
  • HPTR full with 15.2M parameters. It needs RTX 3090 for training. 
    model.model.intra_class_encoder.n_layer_tf_map=-1 \
model.model.decoder.tf_n_layer=6 \
model.model.decoder.k_reinforce_tl=-1 \
model.model.decoder.k_reinforce_agent=-1 \
model.model.decoder.k_reinforce_all=1 \

Others

  • Different polyline embedding. 
    model.pre_processing.relative.pose_pe.agent=xy_dir \
model.pre_processing.relative.pose_pe.map=xy_dir \
  • Attention without bias. 
    model.model.tf_cfg.bias=False \
  • Different RPE mode. 
    model.model.rpe_mode=xy_dir \
model.model.rpe_mode=pe_xy_dir \
  • Apply RPE to query. It needs RTX 3090 for training. 
    model.model.tf_cfg.apply_q_rpe=True \
  • Without anchor reinforce (17.5M parameters). 
    model.model.decoder.tf_n_layer=3 \
model.model.decoder.k_reinforce_agent=8 \
model.model.decoder.k_reinforce_anchor=-1 \
  • Without anchor reinforce, larger model (23.3 parameters). 
    model.model.n_tgt_knn=50 \
model.model.intra_class_encoder.n_layer_tf_map=6 \
model.model.decoder.tf_n_layer=4 \
model.model.decoder.k_reinforce_agent=8 \
model.model.decoder.k_reinforce_anchor=-1 \